This invention relates generally to methods and apparatus for CT imaging and other radiation imaging systems, and more particularly to utilizing CT images to determine perfusion parameters.
In at least some computed tomography (CT) imaging system configurations, an x-ray source projects a fan-shaped beam which is collimated to lie within an X-Y plane of a Cartesian coordinate system and generally referred to as an xe2x80x9cimaging planexe2x80x9d. The x-ray beam passes through an object being imaged, such as a patient. The beam, after being attenuated by the object, impinges upon an array of radiation detectors. The intensity of the attenuated beam radiation received at a detector array is dependent upon the attenuation of the x-ray beam by the object. Each detector element of the array produces a separate electrical signal that is a measurement of the beam attenuation at the detector location. The attenuation measurements from all the detectors are acquired separately to produce a transmission profile.
In known third generation CT systems, the x-ray source and the detector array are rotated with a gantry within the imaging plane and around the object to be imaged, so the angle at which the x-ray beam intersects the object constantly changes. X-ray sources typically include x-ray tubes, which emit the x-ray beam at a focal spot. X-ray detectors typically include a collimator for collimating x-ray beams received at the detector, a scintillator adjacent the collimator, and photodetectors adjacent to the scintillator. A group of x-ray attenuation measurements, i.e., projection data, from the detector array at one gantry angle is referred to as a view. A scan of the object comprises a set of views made at different gantry angles during one revolution of the x-ray source and detector.
In an axial scan, the projection data is processed to construct an image that corresponds to a two dimensional slice taken through the object. One method for reconstructing an image from a set of projection data is referred to in the art as the filtered back projection technique. This process converts that attenuation measurements from a scan into integers called CT numbers or Hounsfield units, which are used to control the brightness of a corresponding pixel on a cathode ray tube display.
To reduce the total scan time, a helical scan may be performed. To perform a helical scan, the patient is moved while the data for the prescribed number of slices is acquired. Such a system generates a single helix from a fan beam helical scan. The helix mapped out by a fan beam yields projection data from which images in each prescribed slice may be reconstructed.
At least one known CT imaging system utilizes a detector array and a data acquisition system (DAS) for collecting image data. The detector array includes detector cells or channels that each produce an analog intensity signal which is representative of the x-ray energy impinged upon the cell. The analog signals are then supplied to the DAS for conversion to digital signals. The digital signals are then used to produce image data. Detector cell degradation as measured by gain non-linearity typically produces ring or band annoyance artifacts.
CT perfusion methods are utilized to assess the viability of tissue of an organ-of-interest by determining perfusion parameters such as a mean transit time (MTT), a cerebral blood flow (CBF), and a cerebral blood volume (CBV). To determine perfusion parameters, the patient is continuously scanned at the same physical location, i.e., the patient table is stationary, and variations in the reconstructed CT images are measured. The image variations are then utilized to determine the perfusion parameters. Because the patient table is stationary, only a very limited volume of tissue can be examined by the CT scanner. For example, using a single slice CT scanner, sampling at 1000 views/second, the maximum volume that can be examined with a stationary patient table is approximately 10 mm. With a multi-slice CT scanner, the coverage is approximately 20 mm or 32 mm. Typically, a coverage range of 80-100 mm of anatomy is required to determine perfusion parameters.
Flat-panel based volumetric CT (VCT), on the other hand, is capable of covering a larger volume than a multi-slice CT scanner covering approximately 20 cm. A 40 cm by 40 cm flat-panel is capable of examining approximately a 20 cm volume, which is sufficient for a CT perfusion study of a human brain and a heart. A typical readout speed of a panel, however, is 30 views/second. Approximately one-thousand views are needed to ensure artifact-free image reconstruction. The time period to acquire one complete projection set is approximately 33 seconds, which is a protracted length of time compared to MTT and CBF. Even when detector channels in z-direction are ganged together across multiple slices, the acquisition time of a flat-panel based VCT is greater than a typical CT scanner acquisition time of 0.5-1.0 seconds.
Methods and apparatus for generating a difference image to determine perfusion parameters such as a mean transit time, a cerebral blood flow, and a cerebral blood volume utilizing a CT imaging system are described. To generate difference images, a difference projection data set is generated. A first sub-set of the projection data set is obtained when no contrast medium is present in a patient or shortly after the contrast medium is injected into the patient, i.e., before the contrast medium is sufficiently absorbed by the patient to impact collected data. A second sub-set of the projection data set is obtained after the contrast medium is absorbed by the patient, i.e., after up-take of the contrast medium. The difference projection data is generated by subtracting, for each view, the first sub-set of projection data from the second sub-set of projection data. The difference projection data then undergoes image reconstruction processing to generate the difference images. The difference images are then mapped to an image generated using the first sub-set of projection data, and perfusion parameters are determined utilizing the mapped difference image.
In another aspect, a processor in the imaging system is programmed to generate difference images and determine perfusion parameters using the difference images. To generate difference images, a difference projection data set is generated. The processor is configured to obtain a first sub-set of the projection data when no contrast medium is present in a patient or shortly after the contrast medium is injected into the patient, i.e., before the contrast medium is sufficiently absorbed by the patient to impact collected data. A second sub-set of projection data is obtained after the contrast medium is absorbed by the patient, i.e., after up-take of the contrast medium. The difference projection data is generated by subtracting, for each view, the first sub-set of projection data from the second sub-set of projection data. The difference projection data then undergoes image reconstruction processing to generate the difference images. The difference images are then mapped to an image generated using the first sub-set of projection data, and perfusion parameters are determined utilizing the mapped difference image.
In yet another aspect, a computer-readable medium in the imaging system is provided which comprises a record of difference projections used to reconstruct a difference image. To generate difference images, a record of difference projection data set is generated. A record of a first sub-set of projection data is obtained when no contrast medium is present in a patient or shortly after the contrast medium is absorbed by the patient to impact collected data. A record of a second sub-set of projection data is obtained after the contrast medium is absorbed by the patient, i.e., after up-take of the contrast medium. The record of difference projection data is generated by subtracting, for each view, the record of the first sub-set of projection data from the record of the second sub-set of projection data. Difference images are then reconstructed utilizing the records of difference projection data. The difference images are then mapped to an image generated using the first sub-set of projection data, and the perfusion parameters are determined utilizing the mapped difference image.